The Biostatistics and Data Management Core (Core C) will support all of the pediatric heart transplantation research projects with statistical analysis and data management. The Core investigators, Drs. Sheryl Kelsey and Maria Mori Brooks, have met and will continue to meet with clinical and laboratory investigators and collaborate in the design of projects, including sample size calculation, definition of measurements and quality control. Core C will interact with all 4 projects and the other cores. Statistical Analysis Strategies include: For Project 1 "Thymic tolerance," primary analysis will focus on the accumulation of number of rejection episodes comparing those who did versus those who did not receive thymus inoculation, and counting process methodology will be used. For Project 2 "Transplant EBV disease," laboratory measures and clinical events will be analyzed comparing patients with high and low EBV viral loads, and outcome data from an experimental protocol will be presented. For Project 3, "Genetic contributions to graft and patient outcomes," statistical models will be created to describe the relationship between outcomes of rejection and explanatory factors of pharmacogenetic, inflammatory and HLA matching. Significant independent predictors of acute and chronic rejection will be sought. The effect of race on rejection over and above genetic and other factors will be evaluated. For Project 4 "Leukocyte gene expression," the Core will determine the level of agreement between gene expression algorithms for predicting allograft rejection and response to therapy versus the observed clinical outcomes. The Biostatistics and Data Management Core will manage and process clinical data received from local projects in Pittsburgh and receive SAS files of clinical data collected in Pittsburgh but initially processed at the University of Alabama in Birmingham. Patient records from 6 sites in the Pediatric Heart Transplant Study will also be forwarded in SAS files to Pittsburgh for Project 3. Core C will receive laboratory data in ACCESS files locally. Standard procedures developed at the Epidemiology Data Center will be used for editing, managing and integrating various data sets as well as for data quality control. SAS will be the primary statistical software used. The Core investigators will collaborate with project investigators to prepare reports of study results.